What is recorded here?
Organized machine-learning accident risk into five practical research problems: avoiding negative side effects and reward hacking, scalable supervision, safe exploration and robustness to distributional shift.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
The record is the exact six-author 2016 arXiv paper and its research agenda. It is not experimental proof that the proposed approaches solve AI safety, does not cover malicious use or all sociotechnical harms, and does not absorb later alignment work.
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People and systems
Dario Amodei; Chris Olah; Jacob Steinhardt; Paul Christiano; John Schulman; Dan Mané
The named authors contributed to this scoped work; individual effort shares and later applications are not assigned by the byline.
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English catalogue narrative
Amodei and colleagues: concrete problems in AI safety
Organized machine-learning accident risk into five practical research problems: avoiding negative side effects and reward hacking, scalable supervision, safe exploration and robustness to distributional shift.
Scientific scope
The record is the exact six-author 2016 arXiv paper and its research agenda. It is not experimental proof that the proposed approaches solve AI safety, does not cover malicious use or all sociotechnical harms, and does not absorb later alignment work.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Dario Amodei; Chris Olah; Jacob Steinhardt; Paul Christiano; John Schulman; Dan Mané
The named authors contributed to this scoped work; individual effort shares and later applications are not assigned by the byline.